Patent indicators are widely used to assess innovative output. Despite the
large variety of empirical studies in the field, however, the precise meaning
of these indicators and their obvious relation to patent value is still based on
assumptions and intuitions. This paper provides the first empirical test of
patent indicators as value measures in the structural form. It disentangles the
different effects reflected in patent indicators and enhances our
understanding why inventions are valuable at all. Using a newly assembled
data set on European polymer patents, current assumptions on the
innovation incentives set by patentability requirements (novelty, inventive
activity) are tested. The estimations are carried out using a custom-tailored
two stage discrete choice probit model yet unknown in the literature. The
results support the assumptions that novelty and inventive activity enhance a
patent’s value. They confirm the importance of backward citations, family
size, and forward citations as va lue indicators. However, they expand on
and partly break with the respective explanations why patent indicators
correlate with profitability.